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Author Debbich, M. url  openurl
  Title Assessing Oil and Non-Oil GDP Growth from Space: An Application to Yemen 2012-17 Type Journal Article
  Year 2019 Publication International Monetary Fund Abbreviated Journal  
  Volume 19 Issue 221 Pages  
  Keywords Economics; Remote Sensing  
  Abstract This paper uses an untapped source of satellite-recorded nightlights and gas flaring data to characterize the contraction of economic activity in Yemen throughout the ongoing conflict that erupted in 2015. Using estimated nightlights elasticities on a sample of 72 countries for real GDP and 28 countries for oil GDP over 6 years, I derive oil and non-oil GDP growth for Yemen. I show that real GDP contracted by a cumulative 24 percent over 2015-17 against 50 percent according to official figures. I also find that the impact of the conflict has been geographically uneven with economic activity contracting more in some governorates than in others.  
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  Notes Approved no  
  Call Number IDA @ intern @ Serial 2721  
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Author Liu, J.; Cai, J.; Lin, S.; Zhao, J. url  doi
openurl 
  Title Analysis of Factors Affecting a Driver’s Driving Speed Selection in Low Illumination Type Journal Article
  Year 2020 Publication Journal of Advanced Transportation Abbreviated Journal Journal of Advanced Transportation  
  Volume 2020 Issue Pages Article ID 2817801  
  Keywords Public Safety  
  Abstract To better understand a driver’s driving speed selection behaviour in low illumination, a self-designed questionnaire was applied to investigate driving ability in low illumination, and the influencing factors of low-illumination driving speed selection behaviour were discussed from the driver’s perspective. The reliability and validity of 243 questionnaires were tested, and multiple linear regression was used to analyse the comprehensive influence of demographic variables, driving speed in a low-illumination environment with street lights and driving ability on speed selection behaviour in low illumination without street lights. Pearson’s correlation test showed that there was no correlation among age, education, accidents in the past 3 years, and speed selection behaviour in low illumination, but gender, driving experience, number of night-driving days per week, and average annual mileage were significantly correlated with speed selection behaviour. In a low-illumination environment, driving ability has a significant influence on a driver’s speed selection behaviour. Technical driving ability under low-illumination conditions of street lights has the greatest influence on speed selection behaviour on a road with a speed limit of 120 km/h (β = 0.51). Risk perception ability has a significant negative impact on speed selection behaviour on roads with speed limits of 80 km/h and 120 km/h (β = −0.25 and β = −0.34, respectively). Driving speed in night-driving environment with street lights also has a positive influence on speed selection behaviour in low illumination (β = 0.61; β = 0.28; β = 0.37).  
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  Series Volume Series Issue Edition  
  ISSN 0197-6729 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2913  
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Author Wang, J.; Qu, S.; Peng, K.; Feng, Y. url  doi
openurl 
  Title Quantifying Urban Sprawl and Its Driving Forces in China Type Journal Article
  Year 2019 Publication Discrete Dynamics in Nature and Society Abbreviated Journal Discrete Dynamics in Nature and Society  
  Volume 2019 Issue Pages 1-14  
  Keywords Remote Sensing  
  Abstract Against the background that urbanization has proceeded quickly in China over the last two decades, a limited number of empirical researches have been performed for analyzing the measurement and driving forces of urban sprawl at the national and regional level. The article aims at using remote sensing derived data and administrative data (for statistical purposes) to investigate the development status of urban sprawl together with its driving forces. Compared with existing studies, NPP/VIIRS data and LandScan data were used here to examine urban sprawl from two different perspectives: urban population sprawl and urban land sprawl. Furthermore, we used population density as a counter-indicator of urban sprawl, and the regression results also prove the superiority of the urban sprawl designed by us. The main results show that the intensity of urban population sprawl and urban land sprawl has been enhanced. However, the upside-down between the inflow of migrants and the supply of urban construction land among different regions aggravates the intensity of urban sprawl. According to the regression analyses, the driving mechanism of urban sprawl in the eastern region relying on land finance and financial development has lost momentum for the limitation of urban construction land supply. The continuous outflow of population and loosely land supply have accelerated the intensity of urban land sprawl in the central and western regions. The findings of the article may help people to realize that urban sprawl has become a staggering reality among Chinese cities; thereby urban planners as well as policymakers should make some actions to hinder the urban sprawl.  
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  Series Volume Series Issue Edition  
  ISSN 1026-0226 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2379  
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Author Priyatikanto, R.; Mayangsari, L.; Prihandoko, R.A.; Admiranto, A.G. url  doi
openurl 
  Title Classification of Continuous Sky Brightness Data Using Random Forest Type Journal Article
  Year 2020 Publication Advances in Astronomy Abbreviated Journal Advances in Astronomy  
  Volume 2020 Issue Pages 1-11  
  Keywords Skyglow  
  Abstract Sky brightness measuring and monitoring are required to mitigate the negative effect of light pollution as a byproduct of modern civilization. Good handling of a pile of sky brightness data includes evaluation and classification of the data according to its quality and characteristics such that further analysis and inference can be conducted properly. This study aims to develop a classification model based on Random Forest algorithm and to evaluate its performance. Using sky brightness data from 1250 nights with minute temporal resolution acquired at eight different stations in Indonesia, datasets consisting of 15 features were created to train and test the model. Those features were extracted from the observation time, the global statistics of nightly sky brightness, or the light curve characteristics. Among those features, 10 are considered to be the most important for the classification task. The model was trained to classify the data into six classes (1: peculiar data, 2: overcast, 3: cloudy, 4: clear, 5: moonlit-cloudy, and 6: moonlit-clear) and then tested to achieve high accuracy (92%) and scores (F-score = 84% and G-mean = 84%). Some misclassifications exist, but the classification results are considerably good as indicated by posterior distributions of the sky brightness as a function of classes. Data classified as class-4 have sharp distribution with typical full width at half maximum of 1.5 mag/arcsec2, while distributions of class-2 and -3 are left skewed with the latter having lighter tail. Due to the moonlight, distributions of class-5 and -6 data are more smeared or have larger spread. These results demonstrate that the established classification model is reasonably good and consistent.  
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  Series Volume Series Issue Edition  
  ISSN 1687-7969 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2878  
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Author Kii, M., Kronprasert, N., & Satayopas, B. url  doi
openurl 
  Title ESTIMATION OF TRANSPORT DEMAND USING SATELLITE IMAGE: CASE STUDY OF CHIANG MAI, THAILAND Type Journal Article
  Year 2020 Publication International Journal of GEOMATE Abbreviated Journal  
  Volume 18 Issue 69 Pages 111-117  
  Keywords Remote Sensing  
  Abstract Transport demand is one of the essential datasets for urban / transport planning and policy development. However, the full size of travel demand survey requires large amount of cost, therefore the survey is merely conducted in developing countries. Their policy decision might be based on the old and limited datasets. In this study we propose a new approach to estimate transport demand using the night-time light satellite image based on the correlation of these two factors. Taking the case of Chiang Mai Metropolitan area, we found a soft relationship between the night-time light intensity and trip generation/trip attraction. Transport survey data is provided by Chiang Mai University for the year 2016. NOAA provides cloud free monthly composite of night-time light satellite image (VIIRS-DNB) by Suomi-NPP satellite of which resolution is 15 arc-second (about 500m by 500m at equator). It is spatially more precise than zones of travel demand survey and monthly frequency. Applying the relationship between transport demand and night-time light intensity, we propose a method to update the transport demand with higher spatial resolution.  
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  Area Expedition Conference  
  Notes Approved no  
  Call Number IDA @ intern @ Serial 2963  
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